{"id":"W4366703926","doi":"10.2478/vjls-2022-0006","title":"Explainability of Artificial Intelligence Models: Technical Foundations and Legal Principles","year":2022,"lang":"en","type":"article","venue":"Vietnamese Journal of Legal Sciences","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Artificial intelligence; Key (lock); Computer science; Liability; Management science; Engineering ethics; Political science; Engineering; Law; Computer security","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01758623,0.0005820437,0.0008056117,0.003711066,0.002187571,0.007137127,0.002833606,0.003918632,0.004395728],"category_scores_gemma":[0.03905196,0.0008606755,0.001937015,0.001592282,0.01993508,0.01090808,0.005262532,0.005643305,0.0004770147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004884084,"about_ca_system_score_gemma":0.003447475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005160125,"about_ca_topic_score_gemma":0.002832219,"domain_scores_codex":[0.9879805,0.006526534,0.0008262348,0.001171715,0.002938877,0.0005561563],"domain_scores_gemma":[0.9358265,0.04893113,0.003502062,0.00812825,0.002994454,0.0006176012],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00000178076,0.000005640245,0.0001498461,0.00001771082,0.000004776416,0.00003795545,0.0001538682,0.001582882,0.000031264,0.9964469,0.0002637468,0.001303611],"study_design_scores_gemma":[0.000002990429,0.000003374282,0.00006591195,0.00003322997,0.000003372795,0.00002612248,0.00003852774,0.007900923,0.00009412019,0.9891899,0.002636065,0.000005466448],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.02561224,0.002059233,0.889864,0.03916404,0.0001716432,0.0001939257,0.000402945,0.0003385641,0.04219351],"genre_scores_gemma":[0.786723,0.002047198,0.2021599,0.001991611,0.0006059804,0.0004217871,0.0003956082,0.0001226518,0.005532381],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.01758623,"threshold_uncertainty_score":0.09300601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08956895597000328,"score_gpt":0.3262964498248786,"score_spread":0.2367274938548753,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}